%0 Journal Article %A XU Shaojie %A CAO Chuqing %A WANG Yongjuan %T Application Research of Visual SLAM in Indoor Dynamic Scenes %D 2021 %R 10.3778/j.issn.1002-8331.2009-0021 %J Computer Engineering and Applications %P 175-179 %V 57 %N 8 %X

Visual SLAM(Simultaneous Localization And Mapping) is the core technology in the field of mobile robots. The traditional visual SLAM cannot be applied to highly dynamic scenes and the map lacks semantic information. This paper proposes a semantic SLAM method for dynamic environment. Firstly, the convolution neural network is used to detect the area of dynamic objects on the image. Secondly, it extracts feature points on the image and removes feature points in the dynamic area and then computes camera pose using static feature points. Finally, the dynamic objects’ map points are removed for building a global semantic map without interference from dynamic objects. The proposed method is tested on TUM datasets, and results show that the proposed method can improve the accuracy of pose estimation by 88.3% in dynamic scenes and construct semantic map without interference from dynamic objects.

%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2009-0021